药物重新利用的知识图:对数据库和方法的审查
Pablo Perdomo-Quinteiro1, Alberto Belmonte-Hernández1
1Grupo de Aplicación de Telecomunicaciones Visuales, Escuela Técnica Superior de Ingenieros de Telecomunicación, Universidad Politécnica de Madrid, Avenida Complutense 30, 28040 Madrid, Spain.
Briefings in bioinformatics
|September 26, 2024
概括
知识图 (KG) 和人工智能 (AI) 加快了对新疾病治疗的药物重新定位. 这篇评论强调了KG,AI技术,以及可靠药物发现的可解释性.
科学领域:
- 药理学 药理学是指药理学的学科.
- 生物技术是生物技术.
- 计算机科学 计算机科学
背景情况:
- 药物再利用为识别新型治疗剂提供了一个有效的策略.
- 知识图 (KG) 越来越多地被用于发现潜在的候选药物.
研究的目的:
- 审查知名的知识图 (KG) 和它们在药物重用中的作用.
- 探索人工智能 (AI) 技术,以提高药物重定向的效率和精度.
- 强调可解释性和验证在人工智能驱动的药物重用中的重要性.
主要方法:
- 对现有的知识图 (KG) 进行全面审查,详细说明它们的结构和数据源.
- 探索各种人工智能 (AI) 技术,应用于药物再利用.
- 讨论可解释性方法和预测验证策略.
主要成果:
- 知识图 (KG) 提供了一个强大的框架,用于识别药物重用候选人.
- 人工智能技术显著加速和提高药物重定向预测的准确性.
- 可解释性方法提高了人工智能驱动的药物发现的可信度和透明度.
结论:
- 结合KG和AI为药物重用提供了一个强大的方法.
- 可解释的人工智能 (XAI) 对于验证和信任人工智能生成的药物重定向预测至关重要.
- 对验证技术的进一步研究将确保可靠和可理解的药物发现结果.
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